5 citations · 8 across the 3 of their papers we have counts for
3 papers
cs.CV2022★ 5 cited
ImaginaryNet: Learning Object Detectors without Real Images and Annotations
Minheng Ni, Zitong Huang, Kailai Feng +1
Without the demand of training in reality, humans can easily detect a known concept simply based on its language description. Empowering deep learning with this ability undoubtedly…
cs.CV2021★ 2 cited
Performance, Successes and Limitations of Deep Learning Semantic Segmentation of Multiple Defects in Transmission Electron Micrographs
Ryan Jacobs, Mingren Shen, Yuhan Liu +10
In this work, we perform semantic segmentation of multiple defect types in electron microscopy images of irradiated FeCrAl alloys using a deep learning Mask Regional Convolutional…
cs.CV2021★ 1 cited
Boosting Weakly Supervised Object Detection via Learning Bounding Box Adjusters
Bowen Dong, Zitong Huang, Yuelin Guo +3
Weakly-supervised object detection (WSOD) has emerged as an inspiring recent topic to avoid expensive instance-level object annotations. However, the bounding boxes of most existin…